Alzheimer's disease is a progressive, fatal neurodegenerative disorder for which there is no preventative treatment or cure. Over 5 million Americans are currently living with sporadic late-onset Alzheimer's disease; of those diagnosed, 65% are women. While the higher prevalence of women with Alzheimer's is in part due to greater lifespan, there is evidence that for some women the menopausal transition can initiate a process of accelerated aging, characterized by metabolic dysfunction and cognitive decline. Substantial basic discovery research demonstrates that the aging female brain undergoes profound shifts in metabolic capacity and function during the transition leading to reproductive senescence. Proposed herein is a translational research project that builds on this basic discovery research, and aims to elucidate the relationship between whole-body metabolic biomarkers and cognition in a population of menopausal women. For this project, our research group has assembled a repository of longitudinal clinical assessments and biospecimens collected from 643 women in the Early Versus Late Intervention Trial with Estradiol (R01AG-024154). The central hypothesis of this research proposal is that metabolic phenotypes will emerge following the menopausal transition; a subset of these phenotypes will be associated with a decline in cognitive performance, indicative of an at-risk phenotype of sporadic Alzheimer's disease. To test this hypothesis, two specific aims are proposed. The first aim is to develop a panel of metabolic biomarkers at baseline (pre- randomization) and to characterize their association with baseline cognitive function, prior to diagnosis of metabolic or cognitive dysfunction. The second aim builds on this metabolic foundation to specifically determine the trajectories of metabolic phenotypes and cognitive performance over a five-year period, with additional evaluation as to whether these associations are modified by randomization to menopausal hormone therapy. To accomplish these aims, statistical analysis ranging from simple ANOVA/ANCOVA analyses to complex mixed linear effects modeling and K-means cluster analysis will be employed. Completion of the proposed project will require collaboration with a diverse team of clinicians, researchers, nurses, and biostatisticians. Consequently, this research proposal will provide a unique training opportunity in clinical translational bench to bedside research. As Alzheimer's-related changes in the brain are known to begin years or decades before clinically detectable dementia, identification of biomarkers indicating the earliest preclinical changes is increasingly important. By using a systems-level approach, this research project seeks to develop a plasma-based biomarker panel to enable an affordable, rapidly deployable, and clinically relevant strategy to reliably detect an at-risk phenotype of sporadic AD.